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  • 标题:Potential Confounding of Particulate Matter on the Short-Term Association between Ozone and Mortality in Multisite Time-Series Studies
  • 作者:Michelle L. Bell ; Jee Young Kim ; Francesca Dominici
  • 期刊名称:Environmental Health Perspectives
  • 印刷版ISSN:0091-6765
  • 电子版ISSN:1552-9924
  • 出版年度:2007
  • 卷号:115
  • 期号:11
  • 页码:1591-1595
  • DOI:10.1289/ehp.10108
  • 语种:English
  • 出版社:OCR Subscription Services Inc
  • 摘要:Background A critical question regarding the association between short-term exposure to ozone and mortality is the extent to which this relationship is confounded by ambient exposure to particles. Objectives We investigated whether particulate matter < 10 and < 2.5 μm in aerodynamic diameter (PM10 and PM2.5) is a confounder of the ozone and mortality association using data for 98 U.S. urban communities from 1987 to 2000. Methods We a ) estimated correlations between daily ozone and daily PM concentrations stratified by ozone or PM levels; b ) included PM as a covariate in time-series models; and c ) included PM as a covariate as in d ), but within a subset approach considering only days with ozone below a specified value. Results Analysis was hindered by data availability. In the 93 communities with PM10 data, only 25.0% of study days had data on both ozone and PM10. In the 91 communities with PM2.5 data, only 9.2% of days in the study period had data on ozone and PM2.5. Neither PM measure was highly correlated with ozone at any level of ozone or PM. National and community-specific effect estimates of the short-term effects of ozone on mortality were robust to inclusion of PM10 or PM2.5 in time-series models. The robustness remains even at low ozone levels (< 10 ppb) using a subset approach. Conclusions Results provide evidence that neither PM10 nor PM2.5 is a likely confounder of observed ozone and mortality relationships. Further investigation is needed to investigate potential confounding of the short-term effects of ozone on mortality by PM chemical composition.
  • 关键词:confounding; mortality; ozone; particulate matter; PM 10 ; PM 2.5 ; sensitivity analysis
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